High-Throughput Experiments and AI for Advanced Materials Discovery

The Huang Lab at the University of Notre Dame develops high-throughput experimental approaches to accelerate the discovery of advanced materials for clean energy applications, including electrocatalysis, hydrogen production, fuel cells, carbon dioxide conversion, and sustainable chemical synthesis.

Undergraduate researchers will work closely with graduate students, postdocs and the principal investigator to prepare, characterize, and analyze materials using experimental and data-driven methods. Students may participate in catalyst synthesis, high-throughput sample preparation, electrochemical measurements, microscopy, materials characterization, data analysis, and visualization. Depending on their interests and background, students may also contribute to Python programming, machine learning-assisted analysis, automation, or instrument development.

No prior research experience is required. Students who are curious, careful, reliable, and excited to learn modern materials research are encouraged to apply.

Name of research group, project, or lab
The Huang Lab
Why join this research group or lab?

The Huang Lab is a new and highly interdisciplinary research group at the University of Notre Dame, focused on accelerating advanced materials discovery through high-throughput experimentation, electrochemistry, materials characterization, and AI-assisted analysis. Because the lab is newly established, students will have the opportunity to help shape a growing research environment and work closely with a new assistant professor, graduate researchers, and other lab members.

Students in the Huang Lab can expect substantial hands-on training, regular mentoring, and frequent research discussions. Undergraduate researchers will have more opportunities for direct feedback, one-on-one meetings, and close involvement in experimental design, data interpretation, and project planning.

This project is important because discovering better materials is essential for clean energy technologies such as hydrogen production, fuel cells, carbon dioxide conversion, and sustainable chemical synthesis. Our broader research program combines catalyst synthesis, nanofabrication, electrochemical testing, microscopy, automation, and data science to understand how material composition and structure control properties. Students will contribute to active projects while developing skills valuable for graduate school, industry, and careers in energy, materials, chemistry, and engineering.

Logistics Information:
Project categories
Chemical and Biomolecular Engineering
Student ranks applicable
First Year
Sophomore
Junior
Senior
Student qualifications

Students from chemical engineering, materials science, chemistry, physics, electrical engineering, computer science, and related disciplines are encouraged to apply. No prior research experience is required, but successful students should be curious, careful, reliable, and willing to learn new experimental and computational techniques.

Because this project involves laboratory research and teamwork, students should be able to follow safety protocols, keep organized records, communicate regularly with mentors and teammates, and contribute responsibly to a collaborative research environment. Strong work ethic, respect for others, attention to detail, and willingness to ask questions are important.

Prior coursework or experience in chemistry, materials science, electrochemistry, programming, data analysis, CAD, or laboratory work is helpful but not required. Students should be comfortable spending time in a laboratory environment and standing for moderate periods during experiments. All necessary training will be provided.

Hours per week
2 credits / 6-12 hours
3 credits / 12+ hours
Compensation
Research for Credit
Number of openings
5
Techniques learned

Students may learn a range of experimental and data-driven techniques depending on the projects, including:

  • Catalyst synthesis and sample preparation
  • High-throughput materials experimentation
  • Electrochemical measurements and analysis
  • Fuel cell and electrolyzer testing
  • Thin-film deposition and nanofabrication
  • Microscopy and materials characterization
  • Data analysis and visualization
  • Python programming for materials data
  • AI-assisted analysis and machine learning for materials discovery
  • Robotics, automation, and instrument control
  • Scientific communication, teamwork, and project planning
Project start
Fall 2026 or later
This project will use an Expectations and Structure agreement.
Expectations and Structure

Commitment
Students are expected to commit the required number of working hours per week during the semester. A minimum commitment of one semester is required, although students interested in continuing for multiple semesters are strongly encouraged. Students should be reliable, punctual, and proactive in communicating about scheduling, progress, and any challenges that arise.

Research Environment
Research projects may involve a combination of experimental work in materials synthesis and characterization, electrochemical measurements, high-throughput experimentation, automation, machine learning, computational analysis, literature review, and scientific communication. The specific project scope will be tailored to each student’s background, interests, and experience level.

Training and Safety
All students must complete required laboratory safety training before beginning any laboratory work. New students will complete an onboarding period focused on safety, research fundamentals, experimental techniques, and lab expectations. Students are expected to maintain detailed research records and follow all laboratory safety protocols.

Meetings and Progress
Students will participate in regular project meetings and weekly group meetings. Progress updates, data summaries, and research discussions will be expected throughout the semester. Students are encouraged to ask questions, share ideas, and contribute actively to the research process.

What I Look For
Motivation, curiosity, enthusiasm, initiative, teamwork, and a willingness to learn are often more important than prior technical skills. Students who demonstrate strong motivation and research potential may have opportunities to continue into independent research, honors theses, conference presentations, publications, or future graduate research positions.

Contact Information:
Mentors
jhuang32@nd.edu
Principal Investigator
jhuang32@nd.edu
Principal Investigator
Name of project director or principal investigator
Jin Huang
Email address of project director or principal investigator
jin.huang@nd.edu
5 sp. | 0 appl.
Hours per week
2 credits / 6-12 hours (+1)
2 credits / 6-12 hours3 credits / 12+ hours
Project categories
Chemical and Biomolecular Engineering